Natural Product: NPC600888

The Chemical Classification was calculated by Classyfire, a software for chemical taxonomy calculation. Reference: DOI:10.1186/s13321-016-0174-y.

  Chemical Representations

  Calculated Properties

Physi-Chem Properties

MedChem Properties

ADMET Properties (ADMETlab3.0)

ADMET: Absorption

ADMET: Distribution

ADMET: Metabolism

ADMET: Excretion

ADMET: Toxicity

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference

Note for Reference:
In addition to directly collecting NP source organism data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated them from below databases:
UNPD: Universal Natural Products Database [PMID: 23638153].
StreptomeDB: a database of streptomycetes natural products [PMID: 33051671].
TM-MC: a database of medicinal materials and chemical compounds in Northeast Asian traditional medicine [PMID: 26156871].
TCM@Taiwan: a Traditional Chinese Medicine database [PMID: 21253603].
TCMID: a Traditional Chinese Medicine database [PMID: 29106634].
TCMSP: The traditional Chinese medicine systems pharmacology database and analysis platform [PMID: 24735618].
HerDing: a herb recommendation system to treat diseases using genes and chemicals [PMID: 26980517].
MetaboLights: a metabolomics database [PMID: 27010336].
FooDB: a database of constituents, chemistry and biology of food species [www.foodb.ca].



  NP Quantity Composition/Concentration

Organism ID Organism Name Organism Material Preparation Organism Part NP Quantity (Standard) NP Quantity (Minimum) NP Quantity (Maximum) Quantity Unit Reference

Note for Reference:
In addition to directly collecting NP quantitative data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated NP quantitative records for specific NP domains (e.g., NPS from foods or herbs) from domain-specific databases. These databases include:
DUKE: Dr. Duke's Phytochemical and Ethnobotanical Databases.
PHENOL EXPLORER: is the first comprehensive database on polyphenol content in foods [PMID: 24103452], its homepage can be accessed at here.
FooDB: a database of constituents, chemistry and biology of food species [www.foodb.ca].



 Biological Activity

Molecular-level activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

In vitro activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

In vivo activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference





 Experimental ADME

Experiment Model Experiment Tissue ADME Type ADME Relation ADME Value ADME Unit Reference





 Experimental Toxicity

Quantitative toxicity

Experiment Model Experiment Organism Toxicity Type Toxicity Relation Toxicity Value Toxicity Unit Reference

Common Abbreviations:
LC: Lethal Concentration; LD: Lethal Dose; LT:Lethal Time; NOAEL: No-observed-adverse-effect Level; BMDL: Benchmark Dose Lower Confidence Limit; BMD: Benchmark Dose; BMC:Benchmark Concentration; LOAEL: Lowest Observed Adverse Effect Level; RfD:Reference Dose; RfC:Reference Concentration; MRL: Minimal Risk Level; MEG: Maximum Exposure Guideline; PAC: Protective Action Criteria

Categorical toxicity labels

Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption
Hepatotoxicity Carcinogenicity Mutagenicity Cardiotoxicity Respiratory Toxicity Eye Irritation Endocrine Disruption

Note for Reference:
In addition to directly collecting NP quantitative data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated NP toxicity records from domain-specific databases. These databases include:
ToxValDB: a curated database that compiles quantitative toxicity values for chemicals from diverse public sources to support toxicological research and risk assessment.
TOXRIC: a comprehensive, free-to-access, online database providing toxicological/feature data. The toxicity labels are retrieved from this database. [PMID: 36400569]


  Chemically structural similarity

Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes approximately 50,000 NPs with experimentally-derived bioactivity available in NPASS)

Similarity is measured using the Tanimoto coefficient (Tc) , which compares the binary fingerprints of two molecules. Tc is calculated as the intersection divided by the union of '1' bits in the fingerprints, ranging from 0 to 1, with 1 indicating highest similarity.

●  The left chart: Distribution of similarity level between NPC600888 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.5 or Top200).

Similarity Score Similarity Level Natural Product ID
1.0 High Similarity NPC303485
0.8261 Intermediate Similarity NPC121649
0.8143 Intermediate Similarity NPC601565
0.8125 Intermediate Similarity NPC138299
0.8088 Intermediate Similarity NPC150908
0.7714 Intermediate Similarity NPC71061
0.7606 Intermediate Similarity NPC194593
0.7419 Intermediate Similarity NPC231772
0.7222 Intermediate Similarity NPC290830
0.6892 Remote Similarity NPC186227
0.6806 Remote Similarity NPC259757
0.6667 Remote Similarity NPC14606
0.6667 Remote Similarity NPC610480
0.6623 Remote Similarity NPC265624
0.6622 Remote Similarity NPC600972
0.6579 Remote Similarity NPC215203
0.6533 Remote Similarity NPC72425
0.6533 Remote Similarity NPC158027
0.6338 Remote Similarity NPC111112
0.6324 Remote Similarity NPC12200
0.6232 Remote Similarity NPC183950
0.6087 Remote Similarity NPC52005
0.6081 Remote Similarity NPC254351
0.6076 Remote Similarity NPC18699
0.6049 Remote Similarity NPC55443
0.5974 Remote Similarity NPC603508
0.5938 Remote Similarity NPC50898
0.5915 Remote Similarity NPC67322
0.5882 Remote Similarity NPC483773
0.5867 Remote Similarity NPC183
0.5846 Remote Similarity NPC222713
0.5811 Remote Similarity NPC291746
0.5811 Remote Similarity NPC288840
0.5775 Remote Similarity NPC610914
0.5652 Remote Similarity NPC62536
0.5652 Remote Similarity NPC120464
0.5652 Remote Similarity NPC601901
0.5625 Remote Similarity NPC272064
0.5616 Remote Similarity NPC605634
0.56 Remote Similarity NPC112954
0.5522 Remote Similarity NPC279121
0.5507 Remote Similarity NPC52611
0.5507 Remote Similarity NPC156222
0.5507 Remote Similarity NPC29353
0.5488 Remote Similarity NPC205026
0.5455 Remote Similarity NPC78540
0.5455 Remote Similarity NPC196179
0.5443 Remote Similarity NPC248739
0.5432 Remote Similarity NPC159707
0.5429 Remote Similarity NPC184136
0.5429 Remote Similarity NPC59951
0.5429 Remote Similarity NPC241838
0.5429 Remote Similarity NPC266597
0.5417 Remote Similarity NPC606638
0.5385 Remote Similarity NPC603692
0.5375 Remote Similarity NPC601984
0.5366 Remote Similarity NPC143851
0.5352 Remote Similarity NPC603662
0.5286 Remote Similarity NPC600177
0.5256 Remote Similarity NPC34089
0.5211 Remote Similarity NPC234133
0.5139 Remote Similarity NPC600900
0.5125 Remote Similarity NPC606549
0.5072 Remote Similarity NPC274121
0.507 Remote Similarity NPC241498

Similar Clinical/Approved Drugs

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules.

●  The left chart: Distribution of similarity level between NPC600888 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.5 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage
0.5522 Remote Similarity NPD1511 Phase 2

Bioactivity similarity

  Bioactivity similarity

Similar Natural Products in NPASS

Similarity level is defined by Bioactivity similarity was calculated based on bioactivity descriptors of compounds. The bioactivity descriptors were calculated by a recently developed AI algorithm Chemical Checker (CC) [Nature Biotechnology, 38:1087–1096, 2020; Nature Communications, 12:3932, 2021], which evaluated bioactivity similarities at five levels:
A: chemistry similarity;
B: biological targets similarity;
C: networks similarity;
D: cell-based bioactivity similarity;
E: similarity based on clinical data.
Those 5 categories of CC bioactivity descriptors were calculated and then subjected to manifold projection using UMAP algorithm, to project all NPs on a 2-Dimensional space. The current NP was highlighted with a small circle in the 2-D map. Below figures: left-to-right, A-to-E.

A: chemistry similarity
B: biological targets similarity
C: networks similarity
D: cell-based bioactivity similarity
E: similarity based on clinical data